Conventionally, there is a disclosed example of a technique applied to a navigation apparatus to be installed in a vehicle. The navigation apparatus predicts, on the basis of a past trip history of the vehicle, a goal for which the vehicle is heading. The trip history includes start and end points of trips and days and times of the trips (See Patent Reference 1, for example). According to Patent Reference 1, the navigation apparatus searches a past trip history for a record of moving at “20:30, Thursday” when, for example, a driver is traveling in a vehicle at 20:30 on a Thursday. In the case where a search result shows that the vehicle moved to a landmark A three times and a landmark B once at corresponding times and on corresponding days in the past, the landmark A is predicted to be a goal with a high probability of 75%. In the case where there is no record of moving at “20:30, Thursday” in the past, the condition for searching for a history record is eased to, for example, “20:30, weekday” to extract an appropriate record, so that a landmark to be a goal is predicted similarly on the basis of trip frequency. In this example, a “day” of Thursday, is generalized to a larger set (hereinafter referred to as class) of “weekdays”. Similarly, the “time” of 20:30 may be categorized into a defined class such as “evening (18:00 to 24:00)” for the purpose of calculating a prediction probability on the basis of frequency using more history records. Using such classes for prediction is effective not only for the case where there is no record to satisfy a condition but also from viewpoint of increasing reliability of a prediction probability, because referring to more data items in a calculation of probability generally increases reliability.
Patent Reference 1: Japanese Unexamined Patent Application Publication No. 2005-156350